IoT Goes Nuclear: Creating a ZigBee Chain Reaction

By Eyal Ronen, Colin O'Flynn, Adi Shamir, Achi-Or Weingarten. IEEE Symposium on Security and Privacy, 2017

479 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/e79f66525f923afafc004043575f84ebe1a2b6a6

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Citations in the corpus

Edge-computing-driven Internet of Things: A Survey (2022, background): “discovered a new type of worm threat [147].”
SoK: Security Evaluation of Home-Based IoT Deployments (2019, background): “We recognize that there are more powerful adversaries that can attack low-energy (LE) based devices [15], but they require specialized resources that are not available in many home networks.”
Understanding the Mirai Botnet (2017, background): “Researchers have found that IoT devices contain vulnerabilities from the ﬁrmware level [18, 19] up to the application level [26, 29, 73, 78].”
A Review of Intrusion Detection Systems Using Machine and Deep Learning in Internet of Things: Challenges, Solutions and Future Directions (2020, background): “One study [68] demonstrated that an experimental malware attack against Philips Hue smart lamp was so successful that it compromised all such lamps in the network, despite the presence of reliable cryptographic authentication mechanisms against malicious firmware updates.”
Evaluating Critical Security Issues of the IoT World: Present and Future Challenges (2018, background): “In addition, in the same period, researchers uncovered a ﬂaw in the radio protocol ZigBee [6] that has been shown and demonstrated by using an aerial drone to target a set of smart Philips light bulbs in an ofﬁce tower, infecting the bulbs with a virus that let the attackers to turn the lights on an”
A Survey on Internet of Things and Cloud Computing for Healthcare (2019, background): “Based on these distinctive features, Bluetooth and Zigbee are commonly used in IoT and cloud computing for healthcare applications [39].”
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security (2018, methodology): “This situation of nuclear destruction of technology can be described as ‘IoT goes nuclear’ [117].”
A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services (2018, methodology): “3) Use of Common (Or No) Key: In many cases, key management relies on a common key embedded to all the devices of the same model [15].”
Edge Computing Security: State of the Art and Challenges (2019, methodology): “master key) for a particular application, the attacker has the incentive to physically attack one of the devices at a high cost [46].”
End User Security and Privacy Concerns with Smart Homes (2017, background): “Findings include over-privileged applications on smart home platforms and vulnerable devices like locks [32] and lightbulbs [42, 50].”
BlackIoT: IoT Botnet of High Wattage Devices Can Disrupt the Power Grid (2018, background): “A number of recent studies have revealed the vulnerabilities of the Internet of Things (IoT) to intruders [21, 49, 50].”
Machine Learning Based Solutions for Security of Internet of Things (IoT): A Survey (2020, background): “Other new surface attacks are initiated by IoT systems because of a smart technology that is attacked by interdependent, interconnected and social IoT systems [80], [81].”